Data Scientist

Must-Have Skills: AI/ML & Deep Learning: Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). End-to-end model building: data prep, training, evaluation, deployment. Experience with NLP, embeddings, transformer architectures, and LLM fine-tuning. GPT / LLM / Agentic AI: Fine-tuning or prompting GPT-based LLMs. Experience building RAG systems (Retrieval-Augmented Generation). Knowledge of vector databases. Understanding of agentic frameworks (CrewAI, LangChain agents, AutoGen, etc.). Developing multi-agent systems with tools, memory, and planning loops. Airflow for workflow orchestration. Docker for containerization. Kubernetes for scalable deployment. CI/CD for model deployment. Model monitoring and drift detection. API development (FastAPI, Flask). Experience with SQL and NoSQL data stores.